Secure and Efficient Biometric-Based Anonymous Authentication Scheme for Mobile-Edge Computing

doi:10.1109/JIOT.2024.3429397

2024-10-15

PRE

DOI：10.1109/JIOT.2024.3429397

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摘要

En 中文

Currently, the biometric-based authentication schemes have been widely deployed in the mobile edge computing environment to ensure the authenticity of the edge nodes' identities. While some solutions for the mobile edge computing adopting a tripartite architecture employ anonymous authentication to protect the edge nodes' sensitive biometric data and transaction information, these solutions come with their own set of challenges. Specifically, the service provider is unable to hold the edge nodes accountable for any violation committed during the transactions. Moreover, the edge nodes are unable to revoke their identity information stored in the registration center. To address these issues, in this work, we introduce a secure and efficient biometric-based anonymous authentication scheme for the mobile edge computing. Our approach utilizes noninteractive zero-knowledge (NIZK) arguments and linear encryption to achieve anonymity and traceability of the edge nodes' identities, while also using accumulators to implement the revocability of the edge nodes' identities, ensuring that the edge nodes with revoked identities cannot pass the verification of the service provider. Additionally, we design an efficient batch verification protocol to handle anonymous authentication messages for the large-scale edge nodes. The feasibility of the proposed scheme could be proven positively by both of the experimental results and the security analysis. The experimental results show that our approach requires up to 418 ms to create an anonymous identity and 16.2 ms to verify it. The time consumption for batch verification of the anonymous identities of the 1200 edge nodes is only 54.4 ms.

Keyword:

Biometrics (access control)

Authentication

Security

Multi-access edge computing

Encryption

Regulators

Registers

Anonymity

authentication

biometric

mobile-edge computing